ABSTRACT ? Overall Development of invasive breast cancer may frequently progress through a preinvasive precursor called ductal carcinoma in situ (DCIS). DCIS is an extremely common clinical diagnosis that is essentially a disease of screening triggered by the detection of abnormal breast calcifications on mammography. Before the advent of mammography, DCIS was an incidental and relatively uncommon finding. Over 60,000 women in the United States will be presented with this diagnosis each year with relatively weak evidence-based guidance for disease management which ranges from active surveillance to bilateral mastectomy. We propose to compile multi-dimensional and multi-scale information on DCIS to construct a Pre-Cancer Atlas that can be used to better understand the disease but also to better stratify risk of progression, a useful translational endpoint. To do this, we have assembled a team of investigators with deep and complementary clinical, experimental, and quantitative expertise and experience with DCIS and breast cancer in general. Further, we conduct these studies with full consideration of tumor evolution and ecology as it pertains to precancer development and progression. Specific aspects of the proposed Atlas construction include: 1) Several types of DCIS cohorts that will capture spatial and longitudinal information including a prospective clinical trial cohort undergoing active surveillance, 2) Analyses designed to maintain relevant spatial organization of the disease for evolutionary and Atlas building considerations based on 3) Radiologic-histologic-cellular-molecular registration approaches, 4) Characterization at multiple scales including whole tumor, single duct and single cell levels, 5) Characterization of relevant parameters including mutations, copy number changes, methylation, gene expression, and microenvironmental elements including inflammatory cell profiles. 6) Incorporation of the breast cancer intrinsic subtype paradigm into the analytic phase, and 7) Layered, spatial, and longitudinal data visualization. Overall, this work will provide a comprehensive platform to guide the next generation of studies on DCIS and other precancers.